The Integrated Mind: A Unified Architecture for Artificial General Intelligence

Title:The Integrated Mind: A Unified Architecture for Artificial General Intelligence Description:This paper presents Cognitive Geometry, a topological and reflexive architecture for Artificial General Intelligence (AGI), enhanced with modular cognitive subsystems that mirror human mental function. The system models beliefs as dynamic structures on a knowledge manifold and uses a reflexive operator RRR to detect and resolve inconsistencies via homotopy smoothing. Unlike pattern-based statistical AI (e.g., LLMs), this architecture ensures global coherence, explainability, and ethical alignment. Cognitive extensions include: a Valence Lattice for emotionally weighted reasoning a Narrative Engine with an anti-dogma mechanism Dual-core reasoning (heuristic and analytical) an Attention Spotlight modeled as a Global Workspace and an Arbiter Module for cognitive resource governance Other subsystems support triadic memory, concept emergence, sensorimotor simulation, ethical dialectics, social narrative alignment, probabilistic functorial learning, and meta-learning. The architecture is validated through Python implementation and an AGI alignment scenario in healthcare. It concludes with a proposed CogniVerse 6-tuple processing pipeline:Input → K → Γ → Ω → Θ → Action, integrating manifold reasoning, pattern extraction, narrative coherence, and ethical decision-making. Why this work matters:This framework unifies mathematical rigor with human cognitive plausibility. It lays the groundwork for robust, adaptive, socially aligned AGI that is both theoretically principled and empirically testable.